On the tractability of the Brownian Bridge algorithm

Recent results in the theory of quasi-Monte Carlo methods have shown that the weighted Koksma-Hlawka inequality gives better estimates for the error of quasi-Monte Carlo algorithms. We present a method for finding good weights for several classes of functions and apply it to certain algorithms using the Brownian Bridge construction, which are important for financial applications.

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